Author: Médéric Boquien

After a year and a half of hard work we are happy to release a new version of CIGALE. It comes with many new features and bug fixes in addition to various optimizations, making it better and faster all around. In particular we would like to highlight the following:

• All the developments made in X-CIGALE have been merged into CIGALE, which will directly include any future development regarding X-rays. Check out Yang et al. (2020, 2022) for a detailed description.
• New state-of-the-art nebular models made with CLOUDY have replaced the older version (Villa-Vélez et al. 2021). In addition, the respective metallicities of the stars and the gas are now decoupled and it is possible to choose from different electron densities.
• The command line interface is now colorful and animated, including progress bars and summary tables with pcigale genconf/check/run so you have all the information you need at a glance.
• The database format has changed, dropping sqlite. This should be transparent for most users but this means that some limitations have been removed and writing a module to store information into the database is much easier.
• How data are stored in memory has been optimized leading to speedups of up to 50% when building the grid of models.
• A different optimization has led to an improvement of up to 25% in the analysis speed.

Note that the minimum version requirement of Python has been bumped to 3.8 and the rich package has been added as a new dependency. As usual it is very strongly recommended to regenerate any pcigale.ini file with this new version.

Download CIGALE 2022.0

The development of this new version of Cigale was partially supported through the FONDECYT REGULAR grant folio 1170618 and 1211000.

After a year and a half of hard work we are happy to release a new version of Cigale. It comes with many new features and bug fixes in addition to various optimizations, making it better and faster all around. In particular we would like to highlight the following:

• The SKIRTOR AGN models (Stalevski et al. 2016) have been added, complementing the models of Fritz et al. (2006).
• The estimated physical properties are now given with units so there is no ambiguity. Note that for practical reasons they can only be given in the FITS files. It is generally recommended to use these rather than ASCII files.
• It is now possible to easily obtain Bayesian estimates of any band. This can be useful for estimating a flux when preparing an observing proposal for instance.
• The database now includes the JWST NIRCam and MIRI filters by default.
• The pcigale-plots script has been largely rewritten. It is now more modular, flexible, and it brings more clarity, in particular to the SED plots.
• There have been many optimizations. The actual speedup will vary depending on your workload but some computationally expensive steps are now up to 50% faster.

Note that the minimum version requirement of Python has been bumped to 3.6 but version 3.7 or later is recommended for optimal performance. As usual it is very strongly recommended to regenerate pcigale.ini with this new version.

Download CIGALE 2020.0

The development of this new version of Cigale was partially supported through the FONDECYT REGULAR grant folio 1170618.

If you are looking for X-CIGALE (Yang et al. 2020), please refer to the download page.

Leaves falling in the North
Birds singing in the South
Cigale is reborn

We have just released a new version of Cigale. This release is momentous in the history of Cigale as not only does it come with a massive amount of new features (see hereafter), but it coincides with the acceptance for publication of a new paper in A&A describing the code in exquisite detail. At the same time, reflecting the ever expanding nature of Cigale, with have changed to a year-based versioning scheme. The version will be named after the year and the number of the release in this year. So 2018.0 for this version.

While there are too many new features to list exhaustively, we would like to highlight a few of them:

• It is now possible to indicate the distance in Mpc. This is especially useful for galaxies that are not in the Hubble flow.
• Cigale can not only fit passband fluxes but also intensive (e.g., the UV slope, D4000, equivalent widths, etc.) or extensive physical properties.
• In addition Cigale can now also fit emission lines fluxes (and combinations of emission lines such as Hα+[NII] for instance). This can either be done with corrected or uncorrected absorption lines.
• Conversely Cigale also does a Bayesian analysis to estimate fluxes in passbands, which can be useful when preparing observations for example.
• Various modules have been added. In particular two modules now closely implement flexible versions of the Charlot & Fall (2000) and starbust laws (Calzetti 2000) and we have included the flexible delayed+burst/quench module presented in Ciesla et al. (2017).
• There have been numerous optimisations in particular when running Cigale on multiple cores.

Download CIGALE 2018.0

The development of this new version of Cigale was partially supported through grant FONDECYT REGULAR 1170618.

Since the release of version 0.12.0, we have identified a few bugs due to the important architectural changes during the previous development cycle. Version 0.12.1 fixes the photometric redshift mode, fixes the estimation of the physical properties when some invalid models are present, and fixes a crash when plotting the PDF.

Download CIGALE 0.12.1

It has been a very rich and exciting year for Cigale and a new release was long overdue. This wait was really worthwhile and this new version 0.12.0 comes with numerous improvements of all sorts. Among the many notable changes:

• Dust templates generated with THEMIS (Jones et al. 2017) have been contributed by the DustPedia team (Davies et al. 2017). Special acknowledgement to Angelos Nersesian and Frédéric Galliano for creating the dust templates and writing the corresponding module.
• High resolution BC03 models have been added. They can be activated when building the database by adding –bc03res=hr.
• It is now possible to compute the models by blocks when there is not enough memory to compute all of them in one go. There is only a very marginal slowdown.
• The rapid evolutionary phases of stellar populations lasting less than 1 Myr should now be better captured.
• It is now possible to compute additional properties such as the bolometric stellar luminosity.
• Small speed optimisations should make models ~1% faster to compute.

In addition there have been a some under-the-hood modifications in preparation for the new great things coming to Cigale in the next months. Stay tuned!

Download CIGALE 0.12.0

The development of this new version of Cigale was partially supported through grant FONDECYT REGULAR 1170618.

On 10 February 2017 we released version 0.11.0. It comes with various bug fixes and improvements. Among the main changes:

• Nebular models have been improved, refined, and extended towards lower radiation field intensities.
• There is a new module to compute rest-frame quantities such as the UV β slope, IRX, Dn4000, emission lines equivalent widths, and colours & luminosities in any set of bands.
• The handling of filters has seen various improvements and a new set of filters has been added. Run “pcigale-filters list” for a complete list.
• Several optimisations have led up to ~30% in speedup for the computation of the models.
• Fix for a crash with Numpy 1.12 and another one when using upper limits.
• The minimum python version has been bumped to 3.5, however for better performance we recommend using Python 3.6.

Finally as usual we strongly suggest that you regenerate your pcigale.ini file. Let us know if you have any question or comment.

Download CIGALE 0.11.0

On 15 September 2016 we released version 0.10.0. It comes with various bug fixes and improvements. Among the main changes:

• The output files are now always generated in the form of ASCII and FITS tables
• A crash has been resolved when using the m2005 module
• The models are now always computed in the same order, which is particularly useful for comparing different runs with the savefluxes module for instance.
• Various speed optimisations making the code 10-15% faster than before.

Note that as usual, we strongly recommend that you regenerate your pcigale.ini file.

 

Download CIGALE 0.10.0

On 04 April 2016 we released version 0.9.0. It comes with numerous bug fixes and a few optimizations. Among the main changes:

• It is now possible to pass the parameters through a flat file (one line for each model and one column for each parameter).
• The input parameters now undergo a sanity check to ensure that they do not create problems.
• For convenience the output files have been merged into a single file. The parameters are prefixed with “bayes” when estimated from the PDF and with “best” if they come from the best fit. This file is provided both in FITS and ASCII formats.
• For efficiency, the output spectra and SFH are now saved in FITS rather than in VO-table.
• The behaviour of dustatt_calzleit has been modified to ensure that the actual E(B-V) corresponds to that requested in input. The results are unchanged but it means you may need to sample the E(B-V) to higher values now.
• Various fixes to improve the accuracy of the results, in particular when z>0.

Note that pcigale.ini generated with older versions of cigale do not work anymore. They will need to be regenerated with this version.

 

Download CIGALE 0.9.0.